Loading...
Overview of AI and communication for 6G network: fundamentals, challenges, and future research opportunities
Cui, Qimei You, Xiaohu Wei, Ni Nan, Guoshun Zhang, Xuefei Zhang, Jianhua Lyu, Xinchen Ai, Ming Tao, Xiaofeng Feng, Zhiyong
Cui, Qimei
You, Xiaohu
Wei, Ni
Nan, Guoshun
Zhang, Xuefei
Zhang, Jianhua
Lyu, Xinchen
Ai, Ming
Tao, Xiaofeng
Feng, Zhiyong
Author
Cui, Qimei
You, Xiaohu
Wei, Ni
Nan, Guoshun
Zhang, Xuefei
Zhang, Jianhua
Lyu, Xinchen
Ai, Ming
Tao, Xiaofeng
Feng, Zhiyong
Zhang, Ping
Wu, Qingqing
Tao, Meixia
Huang, Yongming
Huang, Chongwen
Liu, Guangyi
Peng, Chenghui
Pan, Zhiwen
Sun, Tao
Niyato, Dusit
Chen, Tao
Khan, Muhammad Khurram
Jamalipour, Abbas
Guizani, Mohsen
Yuen, Chau
You, Xiaohu
Wei, Ni
Nan, Guoshun
Zhang, Xuefei
Zhang, Jianhua
Lyu, Xinchen
Ai, Ming
Tao, Xiaofeng
Feng, Zhiyong
Zhang, Ping
Wu, Qingqing
Tao, Meixia
Huang, Yongming
Huang, Chongwen
Liu, Guangyi
Peng, Chenghui
Pan, Zhiwen
Sun, Tao
Niyato, Dusit
Chen, Tao
Khan, Muhammad Khurram
Jamalipour, Abbas
Guizani, Mohsen
Yuen, Chau
Supervisor
Department
Machine Learning
Embargo End Date
Type
Journal article
Date
2025
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks has emerged as a transformative paradigm. By embedding AI capabilities across various network layers, this integration enables optimized resource allocation, improved efficiency, and enhanced system robust performance. This paper presents a comprehensive overview of AI and communication for 6G networks, with a focus on their foundational principles, inherent challenges, and future research opportunities. We first review the integration of AI and communications in the context of 6G, exploring the driving factors behind incorporating AI into wireless communications, as well as the vision for the convergence of AI and 6G. The discourse then transitions to a detailed exposition of the envisioned integration of AI within 6G networks, divided into three progressive stages. The first stage, AI for network, focuses on employing AI to augment network performance, optimize efficiency, and enhance user service experiences. The second stage, network for AI, highlights the role of the network in facilitating and buttressing AI operations and presents key enabling technologies. We compare wireless network large models with conventional large language models (LLMs), and identify key design principles and components for building wireless network architectures. In the final stage, AI as a service, it is anticipated that future 6G networks will innately provide AI functions as services, supporting application scenarios like immersive communication and intelligent industrial robots. Specifically, we define the quality of AI service, which refers to a framework for measuring AI services within the network. We further summarize the standardization process of AI for wireless networks, highlighting key milestones and ongoing efforts. In addition, we analyze the critical challenges faced by the integration of AI and communications in 6G. Finally, we outline promising future research opportunities that are expected to drive the development and refinement of AI and 6G communications.
Citation
Q. Cui et al., “Overview of AI and communication for 6G network: fundamentals, challenges, and future research opportunities,” Science China Information Sciences 2025 68:7, vol. 68, no. 7, pp. 1–61, Apr. 2025, doi: 10.1007/S11432-024-4337-1.
Source
Science China Information Sciences
Conference
Keywords
6G, AI, AI and communication, AI for network, AI as a service, LLMs, network for AI
Subjects
Source
Publisher
Springer Nature